This invention relates to apparatus and methods for automatically monitoring and evaluating manufacturing processes, and goods made by manufacturing processes. The invention relates to, for example, operations which produce an ongoing stream of outputs such as discrete absorbent articles, for example disposable diapers, effective to absorb body fluids. Such absorbent article products are typically fabricated as a sequence of work pieces being processed on a continuous web, typically operating on a process line. Such absorbent article product generally comprises and absorbent core confined between a moisture impervious baffle of e.g. polyethylene and a moisture pervious body side liner of e.g. non-woven fibrous material. The absorbent articles are typically made by advancing one of the webs along a longitudinally extending path, applying the absorbent core to a first one of the webs, and then applying the second web over the combination of the first web and the absorber core. Other elements such as elastics, leg cuffs, containment flaps, waste bands, and the like are added as desired for the particular product being manufactured, either before, during, or after, applying the second web. Such elements may be oriented longitudinally along the path, or transverse to the path, or may be orientation neutral.
Typical such manufacturing processes are designed to operate at steady state at a pre-determined set of operating conditions. While the process is operating at steady state conditions, the result desired from the process is desirably and typically achieved. For example, where the process is designed to produce a certain manufactured good, acceptable manufactured goods are normally produced when the process is operating at specified steady state conditions.
As used herein, "steady state" conditions represents more than a single specific set of process conditions. Namely, "steady state" represents a range of specified process conditions which correspond with a high probability that acceptable goods will be produced, namely that the products produced will correspond with specified product parameters.
While a conventional such process is operating, sensors are typically used individually at various locations along the processing line to automatically sense various respective parameters with respect to the good being manufactured. For example, in a diaper manufacturing operation, a sensor such as a photoelectric eye may be used to sense the presence or absence of a particular element of the diaper such as an ear, the edges of a waist band, the leading edge of the absorbent core, or the like.
Known analytical models and control models are based on assumptions that errors related to such sensing are negligible, and thus that all determination signals, or absence of such determination signals, including quantitative signals, are in fact accurate representations of the elements purportedly being detected and/or measured.
However, actual operation of many manufacturing processes, including highly automated processes, typically includes the occurrence of periodic, and in some cases numerous, errors in the determination signals. Such errors may be caused by any of a variety of factors. Such factors may be, for example and without limitation, complete catastrophic failure of the sensor, intermittent failure of the sensor, error in sensor calibration, a transient out-of-calibration condition of the sensor, an effective obstruction between the sensor and the element to be sensed, or a loose or broken connection between the sensor and the computer or the other controller to which the sensor is connected, as well as numerous component and process irregularities.
A variety of possible events in the manufacturing operation can cause the production of absorbent articles which fall outside the specification range. For example, stretchable materials can be stretched less than, or more than, the desired amount. Elements can become misaligned relative to correct registration in the manufacturing operation, or improperly folded over, or creased, or crimped, or turn. Timing between process steps, or speed of advance of an element, can be out-of-tolerance. If such non-catastrophic changes in process conditions can be detected quickly enough, typically process corrections can be made, and the variances from target conditions can accordingly be controlled such that the product remains within accepted specification ranges, without having to shut down the manufacturing operation, and preferably without having to cull, and thereby waste, product.
A variety of automatic product inspection systems are available for carrying out routine ongoing automatic inspection of product being produced on a manufacturing line, and for periodically and automatically taking samples for back-up manual evaluation. Indeed, periodic manual inspection and evaluation of product samples is still important as a final assurance that quality product is being produced. However, in high-speed manufacturing processes, the primary tool for ongoing product inspection is one or more computer controlled automatic inspection systems which automatically, namely without direct human intervention, inspect the product being manufactured, preferably inspecting every unit of such product.
Where product is outside the accepted specification range, and should be culled, it is desired to cull all defective product, but only that product which is in fact defective. If too little product is culled, or if the wrong product is culled, then defective product is inappropriately released into the stream of commerce. On the other hand, if product which in fact meets accepted product specification is culled, then acceptable and highly valuable product is being wasted.
Body-fluid-absorbing absorbent articles such as are of interest herein for implementing the invention are typically manufactured at speeds of about 50 to about 1200 articles per minute on a given manufacturing line. Accordingly, it is impossible for an operator to manually inspect each and every article so produced. If the operator reacts conservatively, culling product every time he/she has a suspicion, but no solid evidence, that some product may not meet specification, then a significant amount of in-fact-good product will have been culled. By contrast, if the operator takes action only when a defect has been confirmed using visual or other manual inspection, defective product may have already been released into the stream of commerce before the defective condition has been confirmed.
One way for the operator to inspect the product for conformity with the specification range is for the operator to periodically gather and inspect, off-line, physical samples of the product being produced. Random such inspections stand little prospect of detecting temporary out-of-specification conditions. Where samples are taken by an operator in response to a suspected out-of-specification condition, given the high rate of speed at which such articles are manufactured, by the time the operator completes the inspection, the suspected offensive condition may have existed long enough that questionable or defective product will have either been shipped or culled without the operator having any solid basis on which to make the ship/cull decision. Further, automated manufacturing process controls may have self-corrected the defect condition before the operator can complete the visual inspection and act on the results of such visual inspection. Thus, conventional manual inspection by an operator, while potentially providing the highest level of inspection quality, has little prospect of effectively monitoring and controlling temporary out-of-specification conditions, or of pro-actively controlling processing conditions which run higher than average risk of producing out-of-specification product.
While off-line inspection can be a primary determinant of quality, and typically defines the final quality and disposition of groups of the product, on-line inspection, and off-line evaluation of on-line-collected data, typically associated with certain manufacturing events, may provide valuable insight into both the operational characteristics of the manufacturing process and the final quality parameters of the product, as well as insight into potential pro-active improvements in process control.
Thus, in processes that operate at speeds such that manual inspection of each unit of product is an unrealistic expectation, the primary mechanism for inspecting each unit of product is one or more computer controlled automatic inspection and control system, backed up by periodic manual inspections to confirm the accuracy of the decisions being made by the automatic inspection and control systems. Such automatic inspection and control system automatically, namely without direct human intervention, inspect the product being manufactured, preferably inspecting every unit of such product.
Automatic inspection and control systems rely on a plurality of sensing devices and analytical tools to detect a corresponding plurality of different, pre-selected parameters, qualitatively and typically quantitatively, in the goods being produced. Such pre-selected parameters are selected for their prospects of representing the actual overall degree to which the goods confirm to pre-selected specifications. Accordingly, the conclusions reached, and the control actions taken on the basis of such conclusions, are only as reliable as the determination signals created and/or developed by the respective sensing devices and analytical tools. The reliability of such determination signals is thus critical to the ability of the automatic inspection and control system to sufficiently and efficiently control the manufacturing operation.
While sensors and analytical tools are readily available for use in automatic inspection and control systems, typical such sensors and analytical tools must be carefully manipulated, such as positioned, mounted, calibrated, programmed, and the like, and so maintained in a manufacturing environment.
As a practical matter, such sensors and tools periodically develop and/or transmit erroneous determination signals, in spite of a regular maintenance program. In typical situations, the inspection and control system is unable to detect the fact that such signals are erroneous signals, whereby the inspection and control system fails by responding, erroneously, as though the signals were in fact accurate, or fails by not responding at all. Such erroneous responses can result in the control system being the cause of product being in fact out-of-specification. Namely, since the automatic control system manages first level inspection decisions, an error in the control system can actually result in release and shipment of product which does not meet accepted specification ranges. So it is critical that the incidence of errors, particularly erroneous determination signals, be limited as much as possible.
As indicated above, there are both advantages and limitations to automatic inspection and control systems. A significant advantage is that the speed of analysis enables such system to inspect each and every unit being fabricated on manufacturing lines that produce up to about 1200 units per minute. Such automatic inspection and control systems are required where rate of product manufacture exceeds the rate of reasonable human/manual inspection, even allowing for multiple humans to do inspections.
a limitation of automatic inspection and control system is that, while such systems conventionally may have the ability to distinguish an accurate determination signal from an erroneous determination signal, they cannot compare, correct, or compensate for erroneous signals. And while erroneous signals do not happen often enough to suggest that such automatic inspection and control systems have no net value, to the extent the incidence of erroneous signals can be reduced, or to the extended the incidence of accepting erroneous signals as accurate can be reduced, the value of such automatic inspection and control systems will be enhanced.
It is an object of this invention to provide improved inspection and control systems, and methods of measuring parameters so as to increase reliability of the decisions made from processing of the determination signals created and/or developed by such inspection and control systems.
It is another object to provide inspection and control systems, and methods of use, which effectively analyze the determination signals and automatically correct for certain defective signals and signal conditions.
It is yet another object to provide inspection and control systems, and methods of use, which effectively modify the determination signal input when the control system detects a defect in the signal.
It still another object to provide inspection and control systems, and methods of use, which detect out-of-calibration sensors and/or analytical tools, and automatically recalibrate such sensors and/or tools.
It is a further object to provide inspection and control systems which automatically implement back-up inspection of the goods associated with defective determination signals.
It is an overall object to provide inspection and control systems which reduce the incidence of erroneous signals being provided to the controller of the manufacturing operation.
It is a more specific object to provide inspection and control system which reduce the incidence of erroneous signals being accepted as accurate by the controller of the manufacturing operation.